Convolutions
PP-OCR
Introduced by Du et al. in PP-OCR: A Practical Ultra Lightweight OCR SystemPP-OCR is an OCR system that consists of three parts, text detection, detected boxes rectification and text recognition. The purpose of text detection is to locate the text area in the image. In PP-OCR, Differentiable Binarization (DB) is used as text detector which is based on a simple segmentation network. It integrates feature extraction and sequence modeling. It adopts the Connectionist Temporal Classification (CTC) loss to avoid the inconsistency between prediction and label.
Source: PP-OCR: A Practical Ultra Lightweight OCR System
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Optical Character Recognition (OCR) | 2 | 66.67% |
| Computational Efficiency | 1 | 33.33% |
Usage Over Time
Components
| Component | Type |
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|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
